Precision radiation therapy (RT) planning relies on patient models that accurately represent the geometric distribution of cancerous and normal tissues, and which provide information to estimate the radiation transport of the treatment beams through the patient. Computed tomography (CT) scanning has been the primary means of providing these patient models, due to its reasonably known geometric accuracy and relationship between image signals and radiation attenuation. Significant limitations exist with radiation therapy based on CT, however, due to its lack of soft tissue contrast for adequately discriminating tissue types. Magnetic resonance imaging (MRI) not only provides improved contrast between tissue types, it also may serve as an important physiological and molecular biomarker for therapy assessment and adaptation, and may more conveniently assess physiological movement of organs and tumors.
Therefore, it is desirable to develop techniques for generating patient models from magnetic resonance imaging to support treatment planning for radiation therapy. This section provides background information related to the present disclosure which is not necessarily prior art.